healthcare

Comments on Article- “Predictive analytics showing the shape of things to come”- The Australian June 25, 2013

The Australian newspaper had an interesting article on June 25, 2013 (http://tinyurl.com/mtah9ju) describing a number of successful predictive analytics applications, but also making the point that market penetration has been slow noting “… despite the numerous uses of predictive analytics, uptake is limited. According to Gartner, only 13 per cent of organisations report extensive use, while fewer than 3 per cent use prescriptive capabilities such as decision/mathematical modelling, simulation and optimisation market”. I posted brief summary comments today in response to the article and am pleased to share a complete copy of my comments:

Excellent article and clearly summarizes the challenges we face in educating management on how PA solutions can help companies improve performance and mitigate risk. I am pleased to share the following 3 observations. My comments are based on my position as CEO of InferX Corporation, a publicly traded predictive analytics company, and serving as adjunct professor teaching MBA strategy courses in the RH Smith School of Business at the University of Maryland.

No. 1   Analytics complements ‘traditional management’

Define your mission; assess external environment and competition using PEST, Porter’s 5 Forces model, other tools; assess internal resources and capabilities; develop detailed value chain analysis; analyze product life cycles; develop cost leader/differentiation global strategies based on product, market, competition and other factors. Analytics can make a major contribution throughout the ‘traditional’ management process. Yet market analysis shows about 85% of the total PA market today addresses the CRM sector. We need to view PA within the context of traditional management rather than a separate ‘big data/analytics’ sector. Integrating PA into traditional management processes is a challenge and the real opportunity with high upside

No. 2   Analytics costs more

True. When the e-commerce revolution emerged years ago, we had major push back from companies who preferred to continue to process orders manually, work with suppliers using ad hoc systems, and avoid ‘costly’ new systems implementation and industry standards. Systems costs did increase, but we created process and performance efficiencies that improved profitability and reduced risk. Today’s analytics solutions demand understanding ROI (and how to measure) and clearly communicating this message.

No. 3    “Analytics Drives Strategy and Strategy Drives Analytics”

Properly executed and integrated into a company’s management processes, I see great opportunity to use analytics to drive strategy, particularly in shaping new product and market innovations to increase ROI. Look at Capital One, an analytics driven competitor reportedly doing 300+ analytic scenarios daily to optimize financial offerings. Or Progressive, capturing motorcycle rider clients using analytics to define a segment with both claims and expense ratios providing strong returns. Amazon, Netflix and many others are using analytics to drive ‘micro-marketing segmentation’ which is where we are heading. And these new strategies create new analytics, enabling analytics- savvy companies such as Amazon to continue to excel.

Clearly all ‘analytics solutions’ providers, a term I prefer to emphasize PA’s broader role, have a challenge ahead- to educate clients, particularly at the ‘C’ level, on the opportunities embracing these solutions and the challenges they will face if they do not. Exciting times lie ahead in the global analytics solutions business for both solutions providers and all companies in all sectors.

Paul B. Silverman

President and CEO

InferX Corporation (OTC/PK: NFRX)

 

Paul B. Silverman writes about entrepreneurship, healthcare, analytics, and strategy management and serves as Advisor, Speaker, Educator, and Managing Partner of the Gemini Business Group, LLC, a new venture development firm, and author of “8 Building Blocks To Launch, Manage, And Grow A Successful Business.” He also serves as Adjunct Professor in the School of Business at George Mason University. See more at Paul B. Silverman Blog and sign up for Entrepreneurship Today! email updates to track latest new venture developments.

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Understanding ‘Unknown- Unknown’ Information Drivers Addresses ‘Sea of Data’ Issues and Creates Opportunities

Understanding The ‘Unknown- Unknown’ Information Drivers Addresses ‘Sea of Data’ Issues and Creates Opportunities

I posted comments on Fast Company article discussing ‘Sea of Data’ issues Fast Company Article “Avoiding Short-Term Thinking In A World of Big Data”   http://tinyurl.com/7gaepbl

I shared my vision that predictive analytics is ‘raising the bar’ in how we manage the ‘sea of data’,  and offered comments on new directions I see in manufacturing and health care. Here is a copy of my comments posted on the Fast Company site:

The article makes the point that “…in a sea of data, how can we make sure that we’re not just reacting to the information in front of our face, but rather analyzing every possible input.”

One solution to the problem, not mentioned in the article, is the need to develop new analytics to identify key drivers which create the data ‘outcomes’. Predictive analytics enable us to identify these ‘unknown-unknown’ drivers that can only be found by analyzing data, looking for relationships and new rules that emerge developed by analyzing the data. Contrast this to today’s ‘deductive’ approach using expert opinion and well-defined rules.

This ‘data-driven’ analysis to create new rules is an inductive (rather than deductive ‘expert opinion’ based approach) and from my perspective holds great promise to radically change current business processes, improve productivity and improve our quality of life.

This may sound bold, but as the former CEO of an early stage predictive analytics company and also looking at new opportunities in analytics, I see exciting potential here.

Some possibilities:

Look at manufacturing. If a “supplier’s supplier” has a problem, supply chain management ensures quick notification, before it impacts the assembly line. Predictive analytics engines ‘raise the bar’ here by analyzing historical performance and risk data, often real time, defining future risk and performance drivers, and enabling management to optimize performance and mitigate risk.

Going beyond traditional data mining, these new predictive analytics tools analyze industry reports, government filings, trade press, and other sources to assess supplier “health,” pending regulations, and other “unstructured” data sources. Seamlessly integrating with other data, we can use these to more accurately gauge supplier and production line risk and improve performance.Driving new rules,  providing real time early warning signs that impact future supplier and business performance are the new management tools to harness ‘the sea of data’.

Look at health care, my primary focus, where PA techniques hold great promise to help our current health care system. Consider the benefits of these new capabilities which are only a small sample of what lies ahead here:

•    Tracking  Medical Diagnoses, Treatments, Medications, Outcomes, Costs,Reimbursements, and Relationships

ICD or International Classification of Disease Codes , classifies diseases on health records.CPT or Current Procedural Terminology codes developed by the AMA describe services provided by medical practitioners. Medicare employs a similar system, using ‘HCPCS’. Tracking and examining relationships among these metrics, looking at patient data, identifying processes, and key cost and patient health drivers, you can develop ‘best practices’ to improve the health
care process.

•    Identifying Adverse Drug Analyses – assessing underlying drivers to more effectively identify “at risk” patients

•    Optimizing clinical trials (candidate selection and monitoring) – predicting higher risk clinical trial candidates and assessing the key risk drivers

•    Developing directional indicators to predict the underlying drivers for treatment of chronic disease to understand how medication protocols impact treatment plans and patient outcomes

The new predictive analytic-based tools now emerging in all sectors are helping companies cope with the sea of data problem, and  “raising the bar” in how leading firms optimize business performance in today’s  dynamic global markets.

Paul B. Silverman

Paul B. Silverman writes about entrepreneurship, healthcare, analytics, and strategy management and serves as Advisor, Speaker, Educator, and Managing Partner of the Gemini Business Group, LLC, a new venture development firm, and author of “8 Building Blocks To Launch, Manage, And Grow A Successful Business.” He also serves as Adjunct Professor in the School of Business at George Mason University. See more at Paul B. Silverman Blog and sign up for Entrepreneurship Today! email updates to track latest new venture developments.

Email:      paul@paulbsilverman.com
blogs:       https://paulbsilverman.com/blog/
Linked in:  Paul Silverman
Twitter:     globalbizmentor

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Buy Health Monitoring Devices Off The Clothing Rack?

In my recent  book, I talked about how technology is reshaping traditional markets and strategies. Given new directions in integrating health care monitors into clothing, I suggested we may be buying health care monitors in Lands End, and discussed how this will impact traditional retailer strategies. Sales staff questions may move from “What size and color jacket would you like to see?” to “Can I show you our blood pressure-only monitoring jacket or our top of the line full featured model tracking glucose, oxygenation and includes a USB port?”

And what about health care coverage. Expect to see some interesting issues emerge here- are you buying a jacket or a medical device; where do you draw the line?

The recently announced MisFit Wearables, with an investment by John Sculley MisFit Wearables Health Care Startup , I expect is moving in this direction joining other players and more are coming. The proliferation of sensor data from a wide range of devices (some you wear as clothes, some you attach to your body, some are like  band-aids, you use and dispose), and the need to track, securely manage, share, analyze and communicate  this data is spawning a new sector.

What is really exciting is moving from collection of basic vital sign data and using advanced analytics to analyze vital sign data, understand the real time impact of medications (both pharmaceuticals and nutraceuticals) and empower users and clinicians with new tools that can, I believe make a real contribution to improve our personal health and wellness, a market sector I am pursuing with a talented team. Lots of exciting developments here. Stay tuned.

 

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